85 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Argonne
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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field. Solid knowledge, and independent research capability in optimization, computing, power system engineering with track records of publications. Proficient in implementing control and optimization
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services for leadership computing facilities Strengthen ALCF’s role in shaping human-centered AI systems for science, bridging visualization, AI, and HPC Contribute to DOE-wide efforts in AI-ready workflows
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The position is part of a new collaboration between Argonne National Laboratory, the University of Notre Dame, and UIUC, supported by the Quantum Information Science Enabled Discovery 2.0 (QuantISED
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have a strong background in fundamental electrochemistry, with preferable hands-on expertise in computational materials science. The applicant should be well versed in code development, application of AI
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artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision Higgs and Standard Model measurements, and searches
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees
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-be completed (typically within the last 0-5 years ) Ph.D. in engineering, operations research, computer science, applied mathematics, or a related field. Demonstrated expertise in mathematical